AI Engineer (Enterprise Automation)
Summary
Design, develop and deploy AI-powered automation agents and ML models that streamline enterprise workflows across functions like finance, HR and shared services. Core stack: Python, SQL, Microsoft Azure AI/ML, Power Platform (Power Automate, Power Apps, Copilot Studio), plus LLMs with RAG and prompt engineering.
About the Role
We are looking for an experienced AI and Machine Learning Engineer to develop intelligent automation solutions that improve business operations across enterprise functions. This role combines AI engineering, machine learning and data analytics to build scalable AI-powered applications that enhance decision-making and streamline workflows.
You will collaborate with business stakeholders, analytics teams and technical specialists to design, deploy and continuously improve AI solutions using modern cloud and automation technologies.
Key Responsibilities
- Design, develop and deploy AI-powered agents to automate business processes and operational workflows.
- Integrate AI solutions with enterprise applications and business platforms through APIs, workflow automation tools and system connectors.
- Build monitoring and observability capabilities to measure AI agent performance, usage and operational effectiveness.
- Develop knowledge-aware AI solutions using techniques such as retrieval-augmented generation, prompt orchestration and contextual reasoning where appropriate.
- Ensure AI solutions follow security, governance, version control and audit requirements throughout the deployment lifecycle.
- Analyse business and operational datasets to identify trends, optimisation opportunities and automation use cases.
- Build and evaluate machine learning models for use cases such as anomaly detection, forecasting, predictive analytics and risk assessment.
- Deploy machine learning models into business intelligence platforms or AI applications using cloud-based machine learning services or Python-based solutions.
- Partner with analytics teams to convert model outputs into dashboards, reports and actionable business insights.
- Monitor solution performance, measure business impact and continuously optimise AI models through data-driven evaluation.
- Work closely with business analysts and domain experts to translate operational requirements into AI models and automation workflows.
- Collaborate with data teams to ensure high-quality, reliable and well-governed data for AI initiatives.
- Maintain clear technical documentation for AI models, pipelines, prompts and deployment processes to support governance and ongoing maintenance.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence or a related discipline.
- At least four years of experience in AI engineering, machine learning, data engineering or intelligent automation.
- Strong programming skills in Python and SQL.
- Hands-on experience with Microsoft Power Platform, including Power Automate, Power Apps, Copilot Studio or related technologies.
- Experience building machine learning models, including regression, classification, clustering, anomaly detection and time-series forecasting.
- Familiarity with Microsoft Azure, including Azure AI services, Azure Machine Learning or other cloud-based AI and machine learning services.
- Understanding of large language models, retrieval-augmented generation, prompt engineering and AI agent development is highly desirable.
- Experience working with both structured enterprise data and semi-structured data such as documents or system logs.
- Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
- Experience supporting Finance, HR, Shared Services or other enterprise business functions would be an advantage.